Prioritizing a research agenda on built environments and physical activity: a twin panel Delphi consensus process with researchers and knowledge users.

BACKGROUND: The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.g., policy makers, practitioners). METHODS: Between September 2022 and April 2023, a three-round, modified Delphi survey was conducted among two independent panels of international researchers (n = 38) and knowledge users (n = 23) to identify similarities and differences in perceived research priorities on the built environment and PA and generate twin 'top 10' lists of the most important research needs. RESULTS: From a broad range of self-identified issues, both panels ranked in common the most pressing research priorities including stronger study designs such as natural experiments, research that examines inequalities and inequities, establishing the cost effectiveness of interventions, safety and injuries related to engagement in active transportation (AT), and considerations for climate change and climate adaptation. Additional priorities identified by researchers included: implementation science, research that incorporates Indigenous perspectives, land-use policies, built environments that support active aging, and participatory research. Additional priorities identified by knowledge users included: built environments and PA among people living with disabilities and a need for national data on trip chaining, multi-modal travel, and non-work or school-related AT. CONCLUSIONS: Five common research priorities between the two groups emerged, including (1) to better understand causality, (2) interactions with the natural environment, (3) economic evaluations, (4) social disparities, and (5) preventable AT-related injuries. The findings may help set directions for future research, interdisciplinary and intersectoral collaborations, and funding opportunities.

Crowdsourcing for Machine Learning in Public Health Surveillance: Lessons Learned From Amazon Mechanical Turk.

BACKGROUND: Crowdsourcing services, such as Amazon Mechanical Turk (AMT), allow researchers to use the collective intelligence of a wide range of web users for labor-intensive tasks. As the manual verification of the quality of the collected results is difficult because of the large volume of data and the quick turnaround time of the process, many questions remain to be explored regarding the reliability of these resources for developing digital public health systems. OBJECTIVE: This study aims to explore and evaluate the application of crowdsourcing, generally, and AMT, specifically, for developing digital public health surveillance systems. METHODS: We collected 296,166 crowd-generated labels for 98,722 tweets, labeled by 610 AMT workers, to develop machine learning (ML) models for detecting behaviors related to physical activity, sedentary behavior, and sleep quality among Twitter users. To infer the ground truth labels and explore the quality of these labels, we studied 4 statistical consensus methods that are agnostic of task features and only focus on worker labeling behavior. Moreover, to model the meta-information associated with each labeling task and leverage the potential of context-sensitive data in the truth inference process, we developed 7 ML models, including traditional classifiers (offline and active), a deep learning-based classification model, and a hybrid convolutional neural network model. RESULTS: Although most crowdsourcing-based studies in public health have often equated majority vote with quality, the results of our study using a truth set of 9000 manually labeled tweets showed that consensus-based inference models mask underlying uncertainty in data and overlook the importance of task meta-information. Our evaluations across 3 physical activity, sedentary behavior, and sleep quality data sets showed that truth inference is a context-sensitive process, and none of the methods studied in this paper were consistently superior to others in predicting the truth label. We also found that the performance of the ML models trained on crowd-labeled data was sensitive to the quality of these labels, and poor-quality labels led to incorrect assessment of these models. Finally, we have provided a set of practical recommendations to improve the quality and reliability of crowdsourced data. CONCLUSIONS: Our findings indicate the importance of the quality of crowd-generated labels in developing ML models designed for decision-making purposes, such as public health surveillance decisions. A combination of inference models outlined and analyzed in this study could be used to quantitatively measure and improve the quality of crowd-generated labels for training ML models.

The influence of removing the 10-minute bout requirement on the demographic, behaviour and health profiles of Canadian adults who meet the physical activity recommendations.

Background: Recently, the Canadian 24-Hour Movement Guidelines for Adults were released, and included a revised physical activity (PA) recommendation. The recommendation of 150 minutes per week of moderate-to-vigorous intensity PA (MVPA) was revised, from requiring that MVPA be accrued in bouts of 10 minutes or more (bouted) to having no bout requirement (non-bouted). The objective of this study was to assess whether there were differences in sociodemographic, health and fitness characteristics of Canadians who met the bouted and non-bouted PA recommendations. Data and methods: Using adult (aged 18 to 79 years) accelerometer data from three combined cycles of the nationally representative Canadian Health Measures Survey (N = 7,102), this study compared adherence to the bouted and non-bouted recommendations. Differences in sociodemographic, health and fitness measures were assessed using independent t-tests and chi-squares. Multivariate linear and logistic regressions controlling for age, sex, household education and smoking examined associations with health and fitness measures. Results: More adults met the PA recommendation using the non-bouted versus bouted (45.3% vs. 18.5%) requirement. Characteristics of those who met the bouted and only the non-bouted recommendations were similar. Exceptions among those who met only the non-bouted recommendation compared with meeting the bouted recommendation included fewer adults aged 65 years and older; lower MVPA, recreation PA and transport PA; and higher sedentary time, light PA and grip strength. Interpretation: Although the removal of the 10-minute bout requirement increased the proportion of Canadian adults who met the PA recommendation, there were no substantial differences in the sociodemographic and health characteristics of the populations captured by the bouted and non-bouted definitions. Results help to inform the transition in reporting for PA surveillance.

How sedentary are Canadian adults? It depends on the measure.

Introduction: The new Canadian 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years and older recommend that adults limit daily sedentary time to eight hours or less, including three hours or less of recreational screen time. The eight-hour recommendation was centred between the evidence from research using self-reported sitting time (threshold: seven hours or less per day) and accelerometer-measured sedentary time (threshold: nine hours or less per day). The purpose of this study is to compare the percentages of Canadians meeting three different sedentary thresholds (three hours or less per day of screen time, seven hours or less per day of self-reported sitting time and nine hours or less per day of accelerometer-measured sedentary time). Methods: This analysis is based on 2,511 adults (aged 18 to 79 years) from Cycle 3 of the Canadian Health Measures Survey, in 2012 and 2013. Screen time and sitting time were assessed via self-report, and average daily sedentary time was assessed using a hip-worn Actical accelerometer. Results: Adults self-reported an average daily screen time of 3.2 hours (95% confidence interval [CI]: 3.0 to 3.5) and an average daily sitting time of 5.7 hours (95% CI: 5.4 to 6.0). According to accelerometry data, adults accumulated an average of 9.8 hours per day (95% CI: 9.7 to 9.9) of sedentary time. Adherence varied, with 57.7% meeting the self-reported recreational screen time threshold of three hours or less per day, 71.7% meeting the self-reported sitting time threshold of seven hours or less per day and 26.5% meeting the accelerometer-measured sedentary time threshold of nine hours or less per day. Interpretation: The percentage of Canadian adults meeting the three different sedentary behaviour thresholds varied widely. The findings in this article highlight the difference in sedentary time between what Canadians report versus what is measured by an accelerometer.

Sedentary behaviour surveillance in Canada: trends, challenges and lessons learned.

BACKGROUND: Historical changes in the nature of sedentary activities have been observed in other countries, but it is not clear if similar trends exist in Canada. It is also unclear how changes in the measurement of sedentary behaviour affects national estimates. Our objective is to document all sources and measures of sedentary behaviour from Canadian, nationally representative surveys, and report on selected estimates of time spent in sedentary activities. Lessons learned can benefit the wider international surveillance community. METHODS: We describe and document all data sources of sedentary behaviour at the national level in Canada, and report on selected prevalence data from repeated cross-sectional surveys. We summarize amounts of total device-assessed sedentary time and self-reported sedentary activities (e.g., passive travel, leisure television, computer, video games, screen, and reading) by age group over time. RESULTS: Nineteen national surveys were identified. Changes in questions and/or response categories precluded direct assessment of trends over time for some measures; however, certain trends were observed. Accelerometer-measured sedentary time, leisure reading (among those < 50 years) and television/video viewing in younger age groups have remained relatively stable (with a possible slight decline in television/video viewing). Time spent in passive travel and leisure computer and electronic device use appears to have increased. Television and video viewing appears to have increased in older adults while their leisure reading appears to have fallen. CONCLUSIONS: Changes in measurement of sedentary behaviour can affect estimates and reduce comparability over time. Total leisure screen use appears to have increased over time, reflecting the ways in which Canadians spend their free time and technological advances. The main public health message is the need for continued efforts to reduce leisure screen use, especially among youth and older adults.

Gender and education differences in sedentary behaviour in Canada: an analysis of national cross-sectional surveys.

BACKGROUND: Canadians spend the majority of their days sedentary. Gender and education are important social determinants of health that impact health behaviours. There is evidence that gender and educational differences in sedentary behaviour exist. In Canada, while general trends suggest that leisure sedentary activities have changed; there has been no comprehensive assessment examining whether historical changes in sedentary behaviour differ by gender and education level. Our objective was to examine whether gender and educational differences in accelerometer-measured sedentary time and self-reported sedentary behaviours exist among Canadians and if differences are consistent across age groups, over time and across multiple survey sources. METHODS: We summarize amounts of total accelerometer-measured sedentary time and self-reported sedentary activities (e.g., passive travel, television, computer, video games, screen, reading) by age (i.e. children: 6-11 years, youth: 12-17 years, adults: 18-34 years, 45-49 years, 50-64 years, and older adults: ≥ 65 years), gender (girls/women, boys/men) and household education level (< post-secondary vs. ≥ post-secondary) over time in the Canadian Community Health Survey, Canadian Health Measures Survey, General Social Survey, and the Health Behaviour in School-Aged Children study. Gender and education level differences are examined using independent sample t-tests or chi-square analyses. RESULTS: While few differences were found for total accelerometer-measured sedentary time, gender and education differences in self-reported, type-specific sedentary behaviour were identified. Among youth, data from all surveys consistently identified that boys engaged in more video/computer game play (e.g., boys: 0.35-2.68 vs. girls: 0.09-2.15 h/day), while girls engaged in more leisure reading (e.g., boys: 0.45-0.65 vs. girls: 0.71-0.99 h/day). Those with a higher education or household education often reported more leisure reading and passive travel. Education level differences in screen time were often age dependent, with leisure computer use greater in higher education groups in adults only and leisure television watching generally higher in lower education groups in children and adults, but not youth. CONCLUSIONS: This information is valuable as it helps to identify segments of the population which may be at greater risk for engaging in higher volumes of sedentary behaviour. In turn, this information can identify target audiences and behaviours for policies and interventions. Future work is needed to further understand factors contributing to these differences (e.g., preferences, occupation, family structure).

Measuring Active Transportation on National Health Surveys in Canada From 1994 to 2020.

BACKGROUND: Active transportation (AT), described as self-powered modes of travel (eg, walking and cycling), is an important source of health-promoting physical activity. While AT behaviors have been measured on national health surveys in Canada for over 2 decades, historic prevalence has not been previously reported. We aimed to document the measures of AT on Canada's various national health surveys, examine AT over time, and interpret them within the context of evolving methods of assessment. METHODS: We compiled and summarized the questions used to measure AT among Canadians on 4 national health surveys: National Population Health Survey (1994-1998), Canadian Community Health Survey (2000-2020), Canadian Health Measures Survey (2007-2019), and the Health Behaviour in School-aged Children Study (2010-2018). Among youth and adults (12+ y), we summarized over time: (1) the prevalence of AT participation and (2) time spent in AT (in hours per week) among those who report any AT participation. Where possible, we reported separate estimates of walking and cycling and produced an aggregate estimate of total AT. We stratified results by age group and sex. RESULTS: Changes in AT survey questions over time and between surveys limit the interpretation and comparability of temporal trends. Nevertheless, a consistently higher proportion of females report walking, while a higher proportion of males report cycling. Irrespective of mode, males report spending more total time in AT. Participation in AT tends to decrease with age, with youth reporting the highest rates of AT and young adults often spending the most time in AT. CONCLUSIONS: Monitoring trends in AT can help assess patterns of behavior and identify whether promotion strategies are needed or whether population interventions are effective. Our evaluation of AT over time is limited by questions surveyed; however, consistent differences in AT by age and sex are evident over time. Moving forward, ensuring consistency of AT measurement over time is essential to monitoring this important behavior.

Strength-training and balance activities in Canada: historical trends and current prevalence. / Activités de musculation et d'amélioration de l'équilibre au Canada : historique des tendances et prévalence actuelle.

INTRODUCTION: Muscle-strengthening and balance activities are associated with the prevention of illness and injury. Age-specific Canadian 24-Hour Movement Guidelines include recommendations for muscle/bone-strengthening and balance activities. From 2000-2014, the Canadian Community Health Survey (CCHS) included a module that assessed frequency in 22 physical activities. In 2020, a healthy living rapid response module (HLV-RR) on the CCHS asked new questions on the frequency of muscle/bonestrengthening and balance activities. The objectives of the study were to (1) estimate and characterize adherence to meeting the muscle/bone-strengthening and balance recommendations; (2) examine associations between muscle/bone-strengthening and balance activities with physical and mental health; and (3) examine trends (2000-2014) in adherence to recommendations. METHODS: Using data from the 2020 CCHS HLV-RR, we estimated age-specific prevalence of meeting recommendations. Multivariate logistic regressions examined associations with physical and mental health. Using data from the 2000-2014 CCHS, sex-specific temporal trends in recommendation adherence were explored using logistic regression. RESULTS: Youth aged 12 to 17 years (56.6%, 95% CI: 52.4-60.8) and adults aged 18 to 64 years (54.9%, 95% CI: 53.1-56.8) had significantly greater adherence to the muscle/ bone-strengthening recommendation than adults aged 65 years and older (41.7%, 95% CI: 38.9-44.5). Only 16% of older adults met the balance recommendation. Meeting the recommendations was associated with better physical and mental health. The proportion of Canadians who met the recommendations increased between 2000 and 2014. CONCLUSION: Approximately half of Canadians met their age-specific muscle/bonestrengthening recommendations. Reporting on the muscle/bone-strengthening and balance recommendations elevates their importance alongside the already recognized aerobic recommendation.

Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research.

BACKGROUND: Advances in automated data processing and machine learning (ML) models, together with the unprecedented growth in the number of social media users who publicly share and discuss health-related information, have made public health surveillance (PHS) one of the long-lasting social media applications. However, the existing PHS systems feeding on social media data have not been widely deployed in national surveillance systems, which appears to stem from the lack of practitioners and the public's trust in social media data. More robust and reliable data sets over which supervised ML models can be trained and tested reliably is a significant step toward overcoming this hurdle. The health implications of daily behaviors (physical activity, sedentary behavior, and sleep [PASS]), as an evergreen topic in PHS, are widely studied through traditional data sources such as surveillance surveys and administrative databases, which are often several months out-of-date by the time they are used, costly to collect, and thus limited in quantity and coverage. OBJECTIVE: The main objective of this study is to present a large-scale, multicountry, longitudinal, and fully labeled data set to enable and support digital PASS surveillance research in PHS. To support high-quality surveillance research using our data set, we have conducted further analysis on the data set to supplement it with additional PHS-related metadata. METHODS: We collected the data of this study from Twitter using the Twitter livestream application programming interface between November 28, 2018, and June 19, 2020. To obtain PASS-related tweets for manual annotation, we iteratively used regular expressions, unsupervised natural language processing, domain-specific ontologies, and linguistic analysis. We used Amazon Mechanical Turk to label the collected data to self-reported PASS categories and implemented a quality control pipeline to monitor and manage the validity of crowd-generated labels. Moreover, we used ML, latent semantic analysis, linguistic analysis, and label inference analysis to validate the different components of the data set. RESULTS: LPHEADA (Labelled Digital Public Health Dataset) contains 366,405 crowd-generated labels (3 labels per tweet) for 122,135 PASS-related tweets that originated in Australia, Canada, the United Kingdom, or the United States, labeled by 708 unique annotators on Amazon Mechanical Turk. In addition to crowd-generated labels, LPHEADA provides details about the three critical components of any PHS system: place, time, and demographics (ie, gender and age range) associated with each tweet. CONCLUSIONS: Publicly available data sets for digital PASS surveillance are usually isolated and only provide labels for small subsets of the data. We believe that the novelty and comprehensiveness of the data set provided in this study will help develop, evaluate, and deploy digital PASS surveillance systems. LPHEADA will be an invaluable resource for both public health researchers and practitioners.

Monitoring and evaluating school nutrition and physical activity policies.

Given the increase in the number of Canadian jurisdictions with school nutrition and/or physical activity policies, there is a need to assess the effectiveness of such policies. The objectives of this paper are to 1) provide an overview of key issues in monitoring and evaluating school nutrition and physical activity policies in Canada and 2) identify areas for further research needed to strengthen the evidence base and inform the development of effective approaches to monitoring and evaluation. Evaluation indicators, data sources and existing tools for evaluating nutrition and physical activity are reviewed. This paper has underscored the importance of identifying common indicators and approaches, using a comprehensive approach based on the WHO framework and ensuring that research capacity and funding is in place to facilitate high-quality evaluation efforts in the future.

Evidence synthesis - Where are children and adults physically active and sedentary? - a rapid review of location-based studies. / Synthèse des données probantes - Examen rapide des études spatialisées traitant des lieux d'activité physique et de sédentarité des enfants et des adultes.

INTRODUCTION: Geographical positioning systems (GPS) have the capacity to provide further context around where physical activity (PA) and sedentary time (ST) are accrued especially when overlaid onto objectively measured movement. The objective of this rapid review was to summarize evidence from location-based studies which employed the simultaneous use of GPS and objective measures of PA and/or ST. METHODS: Six databases were searched to identify studies that employed the simultaneous use of GPS and objective measures of PA or ST to quantify location of movement. Risk of bias was assessed, and a qualitative synthesis completed. RESULTS: Searching identified 3446 articles; 59 were included in the review. A total of 22 studies in children, 17 in youth and 20 in adults were captured. The active transportation environment emerged as an important location for moderate-to-vigorous intensity physical activity (MVPA) in children, youth and adults. In children and youth, the school is an important location for MVPA, especially the schoolyard for children. Indoor locations (e.g., schools, homes) appear to be greater sources of lighter intensities of PA and ST. The review was limited by a lack of standardization in the nomenclature used to describe the locations and methods, as well as measures of variance. CONCLUSION: Evidence suggests that the active transportation environment is a potentially important contributor of MVPA across an individual's lifespan. There is a need for future location-based studies to report on locations of all intensity of movement (including minutes and proportion) using a whole-day approach in larger representative samples.

At-a-glance - Conceptualizing a framework for the surveillance of physical activity, sedentary behaviour and sleep in Canada. / Aperçu ­ Conceptualisation d'un cadre de surveillance de l'activité physique, du comportement sédentaire et du sommeil au Canada.

The Public Health Agency of Canada (PHAC) has modernized its approach to physical activity surveillance by broadening its scope to include sedentary behaviour and sleep. The first step was to develop a conceptual framework which covers the full spectrum of physical movement from moderate-to-vigorous intensity physical activity (MVPA) and light intensity physical activity (LPA) to sedentary behaviour and sleep. The framework accounts for the environments in which these behaviours take place (home, work/school, transportation, and community), and applies a socioecological approach to incorporate individual factors and broader built, social, and societal environmental indicators. A visual model of the conceptual framework was created to aid dissemination.

RÉSUMÉ: L'Agence de la santé publique du Canada a modernisé son approche en matière de surveillance de l'activité physique en élargissant la portée de cette dernière de façon à englober le comportement sédentaire et le sommeil. La première étape a consisté à élaborer un cadre conceptuel couvrant toute la gamme de l'activité : activité physique d'intensité modérée à élevée, activité physique de faible intensité, comportement sédentaire et sommeil. Ce cadre tient compte de l'environnement dans lequel ces comportements surviennent (à la maison, au travail ou à l'école, durant le transport entre différents lieux, et dans la communauté) et adopte une approche socioécologique intégrant les facteurs individuels et les indicateurs portant, plus largement, sur les milieux bâti, social et sociétal. Nous avons également conçu un modèle visuel de ce cadre conceptuel pour en faciliter la diffusion.

Developing content for national population health surveys: an example using a newly developed sedentary behaviour module.

BACKGROUND: While physical (in) activity surveillance has grown and continues to grow globally, surveillance of sedentary behaviour is in its infancy. As surveillance evolves to meet the changing nature of these behaviours, there is a need for the development of national health survey questions to provide accurate and consistent measures over time. The development of national health survey content is a complex, detailed and often undocumented process. The objective of this paper is to outline the process that the Public Health Agency of Canada (PHAC) and Statistics Canada took in partnership with academic experts to develop a short, flexible, sedentary behaviour module for the Canadian Health Measures Survey (CHMS) and to provide an approach for the development of future survey content. METHODS: Development of the module followed a multi-step process. The results of this paper describe this process and present a framework for content development. RESULTS: Initially, PHAC and Statistics Canada analysts worked together to identify key content required for a potential survey module. Next, this work was formalized through a contract with academic experts, the scope included a: review of existing Canadian sedentary behaviour modules; literature review linking different sedentary behaviours to health outcomes; and, international scan of modules currently in use in large national health surveys and research. The key output from both review processes was recommendations for a short sedentary behaviour questionnaire module (International Sedentary Assessment Tool). These recommendations provided an evidence-informed basis for discussions about how to revise and update the CHMS sedentary behaviour questionnaire content. Qualitative testing was undertaken and a final module was developed using survey design best practices. CONCLUSIONS: Content volume in national surveys is limited due to demand to measure core content in addition to emerging health topics while keeping surveys as short as possible. Questions must therefore, be concise, valid/reliable, evidence-based, and developed using best practices. The paper describes the development process of a new survey module addressing the emerging area of sedentary behaviour for use in a national survey that may serve as a model for future population survey content development.

By your own two feet: factors associated with active transportation in Canada.

OBJECTIVE: The purpose of this study is to examine socio-demographic, geographic and physical activity correlates of walking and cycling for non-leisure purposes, i.e., to work, school, or errands, in Canada. METHODS: Cross-sectional data from the Canadian Community Health Survey (CCHS) 2003 (n = 127,610) were analyzed using logistic regression to identify factors associated with active transportation. The dependent variables were walking 6+ hours per week and any cycling per week. Independent variables were based on age; marital, education, working and immigrant status; income; geographic location; smoking; and other physical activity. RESULTS: Age and income were associated with both walking and cycling, as was geographic location and other physical activity. The results demonstrated that, while similar, walking and cycling are associated with different factors, and that socio-demographic, geographic and health behaviour variables must be taken into consideration when modelling these transportation modes. CONCLUSIONS: Although walking and cycling are relatively easy means to incorporate physical activity in daily life, these results suggest that it is the young and the physically active who engage in them. This research points to a need to address barriers among those who could benefit the most from increased use of both modes of travel.